{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras import layers\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import glob\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.1.0'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n",
      "11493376/11490434 [==============================] - 0s 0us/step\n"
     ]
    }
   ],
   "source": [
    "(train_images, train_labels), (_, _) = tf.keras.datasets.mnist.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60000, 28, 28)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_images.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('uint8')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_images.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60000, 28, 28, 1)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_images = train_images.reshape(train_images.shape[0], 28, 28, 1).astype('float32')\n",
    "train_images = (train_images - 127.5)/127.5\n",
    "train_images.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "BATCH_SIZE = 256\n",
    "BUFFER_SIZE = 60000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "datasets = tf.data.Dataset.from_tensor_slices(train_images)\n",
    "#datasets #<TensorSliceDataset shapes: (28, 28), types: tf.float32>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "datasets = datasets.shuffle(BUFFER_SIZE).batch(BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generator_model(): #生成器\n",
    "    model = tf.keras.Sequential()\n",
    "    model.add(layers.Dense(7*7*256, input_shape=(100,), use_bias=False))\n",
    "    model.add(layers.BatchNormalization())\n",
    "    model.add(layers.LeakyReLU())\n",
    "    \n",
    "    model.add(layers.Reshape((7, 7, 256)))    #7*7*256\n",
    "    \n",
    "    model.add(layers.Conv2DTranspose(128, (5, 5), strides=(1, 1), padding='same', use_bias=False))\n",
    "    model.add(layers.BatchNormalization())\n",
    "    model.add(layers.LeakyReLU())             #7*7*128\n",
    "    \n",
    "    model.add(layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding='same', use_bias=False))\n",
    "    model.add(layers.BatchNormalization())\n",
    "    model.add(layers.LeakyReLU())             #14*14*64\n",
    "    \n",
    "    model.add(layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', use_bias=False, activation='tanh'))\n",
    "                                              #28*28*1\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def discriminator_model():#判别器\n",
    "    model = tf.keras.Sequential()\n",
    "    model.add(layers.Conv2D(64, (5, 5), strides=(2, 2), padding='same', input_shape=(28, 28, 1)))\n",
    "    model.add(layers.LeakyReLU())\n",
    "    model.add(layers.Dropout(0.3))            #14*14*64\n",
    "    \n",
    "    \n",
    "    model.add(layers.Conv2D(128, (5, 5), strides=(2, 2), padding='same'))\n",
    "    model.add(layers.LeakyReLU())\n",
    "    model.add(layers.Dropout(0.3))            #7*7*128\n",
    "    \n",
    "    model.add(layers.Conv2D(256, (5, 5), strides=(1, 1), padding='same'))\n",
    "    model.add(layers.LeakyReLU())             #7*7*256\n",
    "    \n",
    "    model.add(layers.Flatten())    \n",
    "    model.add(layers.Dense(1)) #此处没有激活，所以计算损失函数时，from_logits=True\n",
    "    \n",
    "    return model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "cross_entropy = tf.keras.losses.BinaryCrossentropy(from_logits=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def discriminator_loss(real_out, fake_out):\n",
    "    real_loss = cross_entropy(tf.ones_like(real_out), real_out)\n",
    "    fake_loss = cross_entropy(tf.zeros_like(fake_out), fake_out)\n",
    "    return real_loss + fake_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generator_loss(fake_out):\n",
    "    return cross_entropy(tf.ones_like(fake_out), fake_out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "generator_opt = tf.keras.optimizers.Adam(1e-4)\n",
    "discriminator_opt = tf.keras.optimizers.Adam(1e-4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "EPOCHS = 100\n",
    "noise_dim = 100 #输入的噪声向量维数（要与之前生产器模型的输入相对应）\n",
    "\n",
    "num_exp_to_generator = 16 #每个EPOCH生产16张图片查看\n",
    "\n",
    "seed = tf.random.normal([num_exp_to_generator, noise_dim])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "generator = generator_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "discriminator = discriminator_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_step(images):\n",
    "    noise = tf.random.normal([BATCH_SIZE, noise_dim])\n",
    "    \n",
    "    with tf.GradientTape() as gen_tape, tf.GradientTape() as disc_tape:\n",
    "        real_out = discriminator(images, training=True)\n",
    "        \n",
    "        gen_image = generator(noise, training=True)\n",
    "        fake_out = discriminator(gen_image, training=True)\n",
    "        \n",
    "        gen_loss = generator_loss(fake_out)\n",
    "        disc_loss = discriminator_loss(real_out, fake_out)\n",
    "        \n",
    "    gradient_gen = gen_tape.gradient(gen_loss, generator.trainable_variables)\n",
    "    gradient_disc = disc_tape.gradient(disc_loss, discriminator.trainable_variables)\n",
    "    generator_opt.apply_gradients(zip(gradient_gen, generator.trainable_variables))\n",
    "    discriminator_opt.apply_gradients(zip(gradient_disc, discriminator.trainable_variables))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_plot_image(gen_model, test_noise):\n",
    "    pre_images = gen_model(test_noise, training=False)\n",
    "    fig = plt.figure(figsize=(4, 4))\n",
    "    for i in range(pre_images.shape[0]):\n",
    "        plt.subplot(4, 4, i+1)\n",
    "        plt.imshow((pre_images[i, :, :, 0]+1)/2, cmap='gray')\n",
    "        plt.axis('off')        \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train(dataset, epochs):\n",
    "    for epoch in range(epochs):\n",
    "        for image_batch in dataset:\n",
    "            train_step(image_batch)\n",
    "        print('.', end='')\n",
    "        if epoch%10 == 0:\n",
    "            generate_plot_image(generator, seed)\n",
    "            \n",
    "    generate_plot_image(generator, seed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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mfXp6umum7VaF1KXLMJNmzZoB1kiwn376KW7rcjPS/v5/Aafaj2oEiqIkvkbg8XjM6T1mzBgAWrduzRNPPAHA//3f/zm6joyhkvFg0gDiyJEjplNwPElPT+fEE08EynenkYGxI0eOBGxfgQyAUSoTiZkIoSD+G/+BPI8++ihgD6r1er1s2bIFwAz1CWfgqVMfimoEiqK4p4uxDDzNyMigVatWAHTu3BmwxmHJoFD5vapsn4pz6MEaVQ2YCUIyRqsiF1xwAWCP6Ra/wKuvvsrf/vY3AA4dOhTzuQb5+fkAvPHGG9StWxewe/rPnTuXd999F7BGZoO933Xr1oUc8nJbHkG0iGYXYzn1p02bZk72YKMVcv/k2XzzzTeD+vsK13L3yLPatWsDcNdddwFw4YUXGlVfHHfV4fP5zLisL7/8EoDzzz/ffGgEiUUfOnSI3/3udwDmQ1RYWBjRBBQnD43/Q+H/2vJ9USNlluFvfvMb8zP50F9xxRV89NFHgC0cYjkTMNgPh6z/uOOOM9Ot69SpA0CTJk0AWLBggZmGLKPoiouLo+KwDVcQyH7EHEtOTjbTmu+8885yPwP7vl100UUAfPzxx5UGtWRlZXHLLbcA8Ktf/QqA+fPnA/bE5FDQduaKogQk7s5CORl69OgBQMOGDavUBOSkk5CYaAFjxowxJ4icov379zeahkhk+ZqVlcWkSZMAK8Tmf+1YIKdIWlpapTbUPp/POC3lhOzSpUu5n4M1FBRg6dKlxzR13ILH46FRo0YAvP322wC0bdvW/Fzui2gGx1KfZaSbmI2RaOEdLjKOrlevXgC88MIL1K9fv9Lv3XzzzQA8+OCDAa9ZUFBgfl9MAXnfPvroI2bPnh3+wqtANQJFUeKnEYjk//bbbwFbak6YMIH+/fsDttRfsWIFzz33HGCHxUQzKC0tJT09HYDevXsD8PLLL5uTQ7QFkdSjRo0Ka2R4uMipXlxcXKmAJj093ZyeMvA0Ly+v3O/4//vQoUOxWXQYZGRksHTpUgCaN29uvi8p0D/++CNg+4PEGVyRE044AYABAwYAlqM03sj9O//88wHIzs6u9DtDhgwxvqhgWbFiBQAHDhwAwgsjBiJugkAeZvmgyiZHjBhh4uSiJvt/CEQVFiHh8/lMXFiEyrJly4yg8P89N1GValtWVmYcRCIMMzMzAeuh8xcix7qGW5APSUpKihnGIWaAz+dj27ZtAJxzzjmANagDoGXLlsbLPmHCBKC80/imm24C3CEIRIiJqZmXl8dZZ50FwCeffAIQshAA+/1atGgRcOyIVyRQ00BRlPiHD53QuHFjoxKWlpYCtho2b948o+ofPnwYsBwu8nuRJNrx9dzcXObNmwfYDjU5DX0+nzk15RRds2ZNKC8TkEjuMzk5mSVLlgDQs2dPub5Rp2fNmnXMv5Xszj179hjt8JVXXgGscGq4RDqPwOv1Gu1nz549QPBaW3p6Oi1atADsuhG5xoIFC0J+rjV8qChKQOIePqwOsTPvv/9+LrzwQsDO2BJN5scff2Tjxo2A7TwbPXq0CbG52Y4WZJ/9+vWjdevWQOVkqoMHDzJjxgwAvvvuu1guLyy8Xq/Zi1+3HHNiVkfDhg2B8tWCQ4YMicIqI0NZWZnxGzjVtOU9ueKKKwArgUy+J76vXbt2AdC+fXvjU4s0qhEoiuJujUCoKgVXvtavX79SEseqVauMLSlhOEnvdCOyvw8//NBoMhJqE//H008/beoghPT0dKPxSAquGzWgBg0aALZ/p6SkpFIkQdbt9Xpp3LgxAF9//TVQXjuSpDGJpkgasluQtW/duhUIrBmItjNo0CCgfEqy+EXkWZgxYwajRo2K7IJ/ISGchR06dODMM88EbCeRNOJITU2tpHqCfQPkqwgCidOHQrSdhR6Ph6uuugqAxx9/vNzPZs+ezeTJkwE7k+3GG280D568ByI4zj77bMcl2BWJ5D69Xq9xbk6ZMgWwHvAvvvgCgJdeegmwM0uHDBli9iT1IlVlG65evRqATp06OVlqlUSj6Khbt26AHfuXIrBAyIf+mmuuMfdQag7EeejxeLj99tsBuzbHKeosVBQlIAmhEXi93konvH/ll0hTORWvueYa/vrXvwK2CikcOXLkmNlrgYhFea5UXm7atAmwT4qSkhKj1UhCUXZ2tsnRr8ohJ6dlsGHGaO0zKysLgGeeeYZTTz0VsM0FCZV5vd5KVX2/vFa5a0lyTcOGDUM2D6KhEfTr1w+ww9tvvfVW2MlsOTk5gBWSrFid6rQqUzUCRVECkhAaQSg0bdoUsJ02/kiee7CaQSw0gosvvhiw6iV+uZb5mWgCkrs/a9YsUwF33XXXARgnHNhaRcuWLYNaQ7T32bZtW5YtWwbYVYf+6cfyTIoDMSkpqZKTWDh8+LBJPAqWSGsEycnJvPfee4C9dkkZjwQHDx40exU/glTZBiLQXhMiauA/6cYpkssuD85rr70GWN1epEhJCpOcOnRiwcKFC6v8flFRkWlScvfddwNWDoV8aKRkVT5g6enp5j1wG2vXrjXOrokTJwL2fVq/fj0LFiwAYPny5YBVij169GjAFvBCSkpKpeKteCJCV5x6kSQzM9OYAk6a9gSDmgaKorjbNMjNzQXgxBNPNG3Iwi0hrl27tsn+Wr9+PeA8BBUL00BCZrt37wbs6szx48fz+uuvA1RqbwW2U3TdunWAFbt/4YUXAExI0imx2KdoZdK9Vzr3Llu2rMp8elGJJc9C/l9aWmrMi2Cr8yJtGiQlJZmw5tq1awF7f5FCMjLFJHQ6o0GdhYqiBMSVPgKxf8SO7NWrl6k+DFcjKCwsNMke/iErt2TkSX657HPlypWA5RisShMQ+7h9+/aAfdIePXo0rFr4aCMOW8kADWTnS2Xp888/D8Dvf/97wGpQIyHXeNdglJaWMnPmTMBK6AIr83Xfvn0Rew3R/KRVX6RQjUBRFHdqBJJOLKG05ORkk245bty4sK7tXzMup9DQoUN56623wrpupJDqQ5H8ctI3atTIhAP9ET+KrF+SdsrKyli1alXU1xspAvmq5Odig0sHqlq1aploymWXXQbY06piTVpaGsOGDQOgTZs2ADz88MOmsjBcdu7caRKJ/MPEkcCVgkDUYunZ36NHD+N0kYdbbr5TJE594MCBSrFoNw05lSxAWZOU4k6bNs2ow5Ib0blzZ6Nay+/J3goKCuKuKkcDcZiOHTsWsMw76esopl68BEFpaanJcpQmMh07djRNZsSBGCyyn9zcXCMQRdBECjUNFEVxZ/hQTjXJ/Lv11ltN1aGowlJZd8YZZ1R7LWmJJU4csNXMqVOnAvCHP/zB0fpjOQpMctY/+OADwNJoRB32z4wU56C8ZxJeatGiRcjNLoPdp39j1WgjjuSnnnoKsMw6mSok4VKnzTuiUWsgmX4y8ej666834U0Ji4oZd9lll1V63zIzM01FpmQlSoiwpKTEhJcjHSpVjUBRFHdqBFX8nekjIO2s5Wtpaak5IcU+y83NLZe7LtcAK/VYpivJ3zklHsNBpYryjjvuqOTbKCsrM6ffJZdcAhCRSThuHoIqGpBMDfJ6vabtuYQYnRKLIaj333+/8e1UN8C3wroAe4aHjLwP9nmtcE13D0ENFnkzg+3dJs63UaNGVds5tzri8QERU2jTpk1m75Lz8NNPP5kPgRQphdOxR9TukpIS1wmCSy+9FMD0bZQP04EDB0wegVN1WeZmFBcXR00QCElJSSYKdvXVVwN2NOxYfP/99wCmVFt6FoaCX1m6mgaKolRPwmkEgpxeK1eupGPHjpV+LmqiONukC3I4oUI3q8yRxG37TEpKMqei9D8UNm7caEJpwfb8j6Zp4BSpmRAt78iRI3GZyaEagaIoiasRxAO3nZTRwo37lOamc+bMAewKzK5du4ZsQ7tBI4gVqhEoihIQ1QiCwI0nZTTQfVampu/VlbUGiU6orbOqmsvgZtzUIkwJDzUNFEWJrWmgKIo7UY1AURQVBIqiqCBQFAUVBIqioIJAURRUECiKggoCRVFQQaAoCioIFEUhxrUGNb1wQ3CyT//Ov/41BsfK349lBqjTfXq9Xt8vvx/dBUUJNxUdyX33er2mMUkkazm06Mil+N/cqm50Iny4EmGNiYK8l/7diWL5/qogcAH+p4HcfP2QKbFEfQSKotRMjcDj8ZCdnQ3YveDDHaceTaQHfu3atc16Q51SpCihoBqBoig1SyOQUdGffvopTZs2BewpyI899hhgz6RzEzLq+vjjj2fjxo1xXo3yv4hqBIqiJE7zUvGsV/zaqFEj/vjHPwJw1VVXAdZYNBmAIl8lLJOTkxPyWLBoNfWUuY6nnXYaH330EQCHDh0Kdnny2gDMmzeP+vXrA3DKKacAziMR2ry0MjV9rwlnGsjcunPOOQewhkx++OGHADRu3BjAjA/3//1HHnkEgAULFpge+dGYKBMK4iy85ppr2Lt3LwDLli0DbNMmIyOD+++/H4C2bdsC0L17dzO5ScZxy4dd/g7grrvuAuC2226L6j4C0bBhQwCaNm3K1q1bAXtWY2ZmJmDt6S9/+Uu5n91zzz189tlnsV5uxKiYGCT/r127Ni1atABg8ODBALRp08YcDFdeeSUAP/zwQ9TXqKaBoiiJYRp4vV5ycnIAe/bd+PHjAXjxxRf5+OOPA15DZswdPHjQSFiRvE6Jlsrct29fAKZPn27Gfou2IlpOoFHaFTl8+LC5hmhFU6dO5eabby53/aqIdCq1nOYy3Rfs8KhoLuIwrWZNgK05BDsC/RjXjKhpUKtWLa6//noA/vSnPwHW/kRr++abbwB77zk5OWbysdyjPXv2MGrUKMAOfYsmFc5nVScdKYoSkITwEeTk5PDAAw8AULduXcCypwEOHDjg6BrifNuwYQNpaWlRWGXobNu2DbAcmxICFb9Bdfh8Po4ePQrAt99+C8BFF11krtmsWTMA40MZNWpUzMOnLVu2ND4Zf0TDkRmGcvplZGRUqf3I9+S9qlevXlTWGw6lpaXk5eUB9umdmppq7mWdOnUAGDt2LACbN282iW7+p/1rr70GwIwZMwBbC96zZ0/U1p4QgmDmzJmcdtppgOUNB+cCoCKzZs0yqpZbeOihhwArj0BUZVHdFy9eDMDw4cODjnbIgyMPUlFRUcxrGCqOMQdrNP17770HwA033ABgVGR/5MM/ZswYnnzyScA2DeT/1113XeQXHSLFxcXccsstALz//vuAlbciwu6mm24CYO3atdVeR0xXMWf9Hb/RQk0DRVHc7SwUB0pRUZGRqhIbD7Z2QE6XQYMGmew9UaedEmlnoZg5EjJMSUnh5ZdfBuCyyy4Lam1VrIE1a9YAcNJJJwGWdtGvX7+AfxvJfdaqVcuYJh06dADgk08+MSaM03wJcb5JKHTnzp0ADBw4MORszGjmEYjT99ZbbzVanbwPgT5zixYtKneNnj17BvPSVaLOQkVRAuJqH8Hy5csBy4kmIZdQqwjbt28PWDUHEq6LN++++y6AcV6WlpYyevTosK4pms/OnTsrhUclfBVLkpOTeeaZZwBM6HLhwoXGOegU0ZrklDzhhBMAePnll43/yI20adOG3bt3A7Z/qzqmTJnCGWecAdgh0lhMnVaNQFEUd2oE4huQZBqwvbCh8vrrrwNWOCcWKZuB8Hg8dO7cGbAl/bp160zySbCIZ1lOTv/wmpwskoQVSwoLC/nqq68A287PzMykVq1aACb8GQhJqxbklHzuuecitdSIIhrPv//9bxM5kXtUVlZW6fclxfjyyy8vl4IM8Nvf/haAf/7zn1FbrysFgXwwxNl12mmnsWLFCiB4Nali0dH8+fOrvBGxxufzMW7cOAAmTJgAwL333hv0dfLz8wFMsZJ/DH7Tpk0AtG7dGqj6AYw2paWlrFy5EoBVq1YB0KRJE7KysgBLUPivraysrNI9Tk5OpmvXrkDlDEsJQ7qVFStWmBL4L7/8ErBNXp/PZ0zWO+64A4D9+/ebPUregQi7xYsX891330VlnWoaKIri7vChqLfLly83ob4xY8YAGAdMoPVLDvuwYcMA6wSRUyhYIh0+FMnfvHlzAK6//nqWLFkC2KaQ7K+kpKTSabho0SJ69+5d7lpsu+GtAAARPElEQVTy+yNHjmTWrFlOllGJaJche71eWrVqBdgVhk2aNAEsLUbMI7lP9erVMxqh/J6o3mJihEIsypC9Xq/Jgj3vvPMAOPnkkwGr5qCgoACwHalz5841msATTzwBWMlkYGkU/fv3D2UZGj5UFCUwrtYIxGm4YsUKY0tJrwFJMZ02bZqxkyW0mJKSYv5WpKskoLz//vuua0wiabOrVq0y9QFVvHalVufi/wD7ZJVaBUnACoVYNCYRTU20vhdffBGAgoICc+/Ebr744ouNo1P+ThygmZmZIYfVYtWYRNb8j3/8A7C12p9//pkHH3wQqLpXhDhIZ8+eDVh7Pf/88wEcVdz6E2ivrhYEQs+ePY2qLHHkN9980/z/3HPPBcqrieJ8EsEhjrNbb72VOXPmAME3Jon2ByQ/P5/58+cDzvLLfT4f1157LYCJ1UeCeHQokjLznj17muxRqZXo27evEQRy/xNJEISKCBDJDC0rKzM1GcEeZmoaKIoSkITQCMCqzAM7XCb5216v16hQgwYNAiA3N9dk0YmqLXFaj8fDgAEDAFi9enVQa4j2SenxeEzfRSm7FmdSbm5uJcfY5MmTTegxksSzZ6HH4zGnvjhABw4caGLoEluXMFq7du0c5yJUxO0agZh+/mFU0WIjrc2qRqAoSuJoBOGyYMECwOroO2TIEMDWKpwSi5NSTgE5FcXXMXHiRGMnS/KQhEQjTby7GMt7II7eoUOHMmXKFMBu2CLhtqlTp9Y4H4HsUb5KOLWsrCzk2ZiqESiKEhBXphhHg+7duwNWD4BwQmvRRk4BCYXK/5s3b260hPXr18dncTEgJSXF1JhIv4YJEyYY34AgEQWv1xvTtvQejyeqVYD+PqxevXoB8PzzzwNWEpUk0kWaGi8IRM2Uh6qsrMwUwbgFWWPPnj1N1pmscfPmzQD07t3bOM/EYVoTadOmjQklSs//HTt2mH/v2rULsJqbQOxmU0g4118QRKN2IykpiW7dugG2IJBQ4ZNPPhk1IaSmgaIoNV8jkOlAwv79+10zIl1O+BEjRgAwadIkEyadO3cuYOfb169f34TJJMRYk5ATt6SkxJz6+/btA6wQqiSESUap/E6s8HfSReNU9q87kUY1P/74I2A3NInmc6sagaIoiR8+9K/Ik71kZGTw7LPPAvYUIXEQduzYMeQBo9GqPpR680svvdScjCL9pcpu/fr1JpVakoyihdN9er1e3y+/H7HXzs3NNbUG0rOgdu3aJu144cKFQGRORzeFD0UL6NKlC506dQJsP8i6deuA6E46SnjToH///qb3nzxAHo/HfMjEoXPPPfcA4RXjRBpZowwASUlJMd+TnvbiLf/Nb34TdQEQLFUJ4XCvlZ2dzeWXXw7YU5y///57oyZLcw8RkLGe0+CPrFmeu+7du5ty+f379wPVOzNTU1NN05js7GzAuu8iAKTbVCz2qKaBoiiJbxokJSWZxh5y+u/Zs8eo2CJppQvy3r17Qw77RCvjTqrLvvrqK5MrIEjoKDs7O2anXzxNg759+/LOO+8AdmZhSUmJOR2lylI0vGB7PPpri6WlpRE1DTIzM01fRlH158yZw+mnny6vB9iNSTIyMvj8888BO1dgx44dlZ7PSIRINbNQUZSAJLxGEEuinYPfoEEDYwOLRnPhhRcCwTeiCId41hqcdNJJfPHFF4CtERQXF5tpRhdffDFgV46Gk9QTTWeh3L8ePXrw9ttvA/aULjnht27datqXff3117Im/9cs9zWae1WNQFEU1QiCId5VebEi3vuUSIm0Mdu9e7c5RSP5vMYqfNinTx/A6o4FdnetOXPmVDkFuiIVqxBDoUa0KnML8f6ARBJRXf3HsPtlzznaZ1JSkg/iMy8hEsRKEIgDWASb5LEUFhZW+96JSeB/j0JFTQNFUQISU41AURR3ohqBoigqCBRFUUGgKAoqCBRFQQWBoiioIFAUBRUEiqKggkBRFFQQKIpCjFuVJUIOfnXUpFqD6tB9ViYaTVhiSY3vWagosSBRBYBT1DRQFEUFgaIoahoocSKSbbhqEmlpaaZFm7RwjwWqESiKUrM0AjldUlNTTftyJf7IfZGWW1lZWTRr1gyw27Vv2LAhPouLAdJhSAahCA0bNuSmm24CYMyYMYDVsFXeL5n92LBhQ8C51iTDcUpKShxPhFKNQFGUxOhZmJSUZPq9VRwllZSUxFtvvQXA4MGDzd/Ivvr37w/YM/PCQePr5XG6T5lheOmllwIwevRoYwevX78egGuvvRaA7du3B7na0IlFz8Lk5GQz7frhhx8G7KE7KSkp5nmWxqRlZWXk5eUB1rMNVvNWwEzKDkStWrXMNWWCdo1oXtq1a1e6du0KwCuvvALYMwyTk5Np06YNYI/MPvnkk03DyGXLlgFw9tlnA4RlMsRDEKSmpgLQqVMncnJyAHsPnTp14ocffgBg27ZtgL3faA7MFJzs0+PxGGE8e/ZswHpQRf2Vdcr/jx49ar4n99h/+pMcACJA8vPzjQodLNEUBLKf3NxcunTpAmDulTgBDxw4YARBVXTv3h2Al156CbDMB5mLGCzavFRRlIAkhEbw2muvcc455wDQsmVLgICngDhmRArv3LkTgA4dOoR8WsZSIxB1WtadlpZmnEWy/orOJ7BVzDp16oQ8+TmS+/R6vbz66qsAXHDBBSGtpzp27NhhZkcWFhYCzrWhaGoEop736dPHmDtr164FnDv9xLm6ZcsWAHJycmjbtm257zlFNQJFUQKSEOHDfv36mek3BQUFjv5GnCTvvvsuAKNGjQISJ2dc7Gk59UtKSpg0aRIATz31FACNGjUycwJFg5BTJDs722hD8aSsrIy7774bgGHDhgG23yMQcq/27NljQmLiL5BT9dNPP6VJkyaArf0dPHgwIhOEw0GevyZNmnDgwIGQriF7kEnJnTp1cvz8B0tCCIJ69eqZBzzYGzxy5EggPCdhLJEHXWLHixYtAmDEiBEm5i4cPnzYeKCPHDkC2B+y008/3URT4s1///tfwN5bamoqTZs2Beyozp///GfAGls/duxYAFauXAlY3vO//OUvAIwfP77ctbdt28auXbsA/D3kUduLU0RQnXjiiSZC8tVXXwHOn0XJP5g8eTJg3WPZY6RR00BRlMRwFhYXFxtNQJwwgZCY65w5cwDo1q0bEN1BkkKo+/R4PEbNlRN+z549jv52ypQpgJ2hVq9evZC1ILflS3Tv3p3FixcDtsazfPlyAM4888yQ72ks8gg++OAD8yyKs1SchsdCNAG/WZShvHQ51FmoKEpAEsJHsG3bNpOb7oTU1FRWrVoFYOzNcDSBaCOOsMmTJ7N161YA7rvvvqCuIZl5FU+TRCY3NxeApUuXVgqVzpo1C3D3fQUrjCsJb/feey8A559/PnDsMGIkNQGnqEagKEpi+Ag8Ho/xgH/++eeALV19Pp/xrPfs2ROw5s9Lyu3FF18MBLbLnBAt27lv374AzJ07l0suuQSAN99809HfSj66f666//dDId4+Aln7unXrADuJDConU4UTJoyFjyA7O9v4qWRfffr0AaqOHng8nkq9GiIRCq0RPQt9Pp9xtHz//fcA3HXXXYD9ZsnvASxevJgXX3wRgEcffRSwTQQ3lrv+/e9/ByyTRvLLnQqCb775ptz/JW8ikenduzcAxx13nPmeCDg5AOKdJ+CUgoICEyKV+/z2228D8N5775n6EXESv/766yYk/PXXXwNW9qRcK1qoaaAoSmKYBlUhapbX6zWng7/zRZxmYiLI6eI0q60qoqUySz1Bbm4uq1evBqwsskCkp6dz6NAhWRsQ3v6EeFZZXnTRRUb7a9y4MWCZBo888ggAd955Z6ReMiamgT8S+v7Tn/4EwOWXX26eS3le9+7dS926dQFbAxBN4vHHHw/5tTV8qChKQBJWI3CKaAsicYcNG2by+IMl0ielaDXiNPJ38EnNuvRYeOGFF+jcuTMAmzZtAmDq1KmccsopgO376NChg5OXrpZYaATNmzcH4J133gGgY8eOck3zO+IAPXr0qHEYivYUCWKtEcgzKKHwwsJC4/SUZ2D27NnGTyRp9bLnpk2bhtzktUY0JgmHK664AoBp06YBcN5557lGEAhSUPXGG28wcOBAoGqvv9wrKWKZO3cuDRo0AODcc88FIlNTEa19isr7r3/9y3ST8v/g+71+ua979+7l5JNPBmzHWSSItSCo2IzlWLz22msADB8+HLC7NrVq1SpqgkBNA0VRar5GIOqYNHLYvn07p512WkjXiocTTSr2fD6fUaeHDh0KQLt27UzTj3nz5kXqJSO+TzkJp06dCsBVV11l7osgJty3335rwmYSUmvWrJnZ84oVK2SNTl66WmKlEdSvXx+w+20GOtVFy1uzZk25vzv11FMrVaA6RTUCRVECkhAJRf6Ic8VpXbZIX0m8ef/996OzsCghVYhgnZaAqcRr166dyap0Kx6Px9QMSLs5n89nTvTDhw8DMGHCBMCq1hNHqYTbhg4dav4tDlM5Ne+77z7jTJs+fTpg+U7EVxLvCUpJSUlGA12yZAlAwFN97969ADzwwAMAXH311QDk5eWFrBEEQjUCRVFiqxE49ZpWhWgC0htfpH8gzjrrLMCuQ5CqxETm448/Bqz3U/oPuJW0tDQGDBgAYKbuHDp0yJzY999/P2Dfl4yMDFq1agXATz/9BNh9/cG+/xJdadu2rdESpG34ueeea9qdh9rANVK0atXKhIDlhJdWc4GQ7lryfkyfPp1evXpFYZUxdhZ6vV4fhCYIJI4sOfgy5+BYSEhOahMkdFWvXj3zgAVLvItxJPtOPkTLly83Ai6SRGKfIvTr169vhLaU427fvt3kCPznP/8BbGdhfn6+MfvESTZjxgxjFskHWwbeZGVlme9Jz8IDBw44esZi4SxMT09n5syZALRu3RrAdCKu5rUAW3CmpaUBVoah1MwEizoLFUUJSExNA0mS8fl8QVePiZNEvkpzz6o69datW9c4ZuRkEBU6VG3ADWzcuLHc/3/3u9/FaSWBkfe9UaNG9OjRA7DNu3379pkQoTwH0uDzu+++Y/PmzYDl9APYvHlzJeewOBmllsStHDlyxNROzJ8/H4Cnn34aOPb9e/bZZwE7s1A0wHHjxkVtnaoRKIoSWx9BSkqKD6yQTrDtmESbEGfR7bffDlh52FLBJTZVSkqK8Q0MGTIEcHfqrVPEZhZ/R1WTjiJBJPeZlpbGl19+CWAmEvl8PlM1OWPGDMBOiFq6dKk57aPdcyDWKcbi4xGt1v/+ic/EP7QqVYribAwHVzUm8f/QByuARE0ST+oJJ5xQ7qv/NQ8fPmz65MfbaxwpUlJSKo1BSwSKi4vNeDr/+glx9kktiKjNhw4dCjn2H05UKhbIsyjOP3/8y8elG5eYCOFQVS1HVahpoChKbDWCikM8g0FUe9EIxBzIzMw015XKtJKSEvP7bj0dgkVi5OB+B5k/Pp/PtOqSyUXt2rUzJ5U4CYPpUh2I9PR0V99/Of3vvPNOY/5I671ITzJyun/VCBRFqfnVh5Ekns7CZcuWceqppwK2Xf3Pf/4z0i8DRH+f/fr14+GHHwbsGpB77rnH/D/cZzItLa1Su6+qHI+xdhbGE00oUhQlIKoRBEE8NQKv12t6ExQWFkb68uWId5g0XLxer4kmiSYgfhV/zUA1ApuEKTr6X6esrCzqAqCmkJycbJyPkq8gGahFRUX6/FWBmgaKosTWNFAUxZ2oRqAoigoCRVFUECiKggoCRVFQQaAoCioIFEVBBYGiKKggUBQFFQSKoqCCQFEUVBAoioIKAkVRUEGgKAoqCBRFQQWBoiioIFAUBRUEiqKggkBRFFQQKIqCCgJFUVBBoCgKKggURUEFgaIowP8DzK/uJwm1WZkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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URUEFgaIoqCBQFIUY5xokUwaXbzUgKaNVXl6esFl5kSSRsw8r49thWYLjgg2S+1/IPpTzU1FRUeNcNenoKPjeTInUC0HxJxF6GSQywZ4f3RocI1iW5bc6Kkoo6J2jKIpuDZIdaXYipb+j3ShDOTZRjUBRFNUIwKmfn5GRAbgrajg95qNJWloaDRs2BNzmoGPGjDE9HaRpy9133w24fRyUxEM8UmlpaXTo0AGA1q1bA7Bhw4awO2LXBtUIFEVJvCrGmZmZNG3aFIBrrrkGgO+++4777rsPcOvaS537OXPmmCaovv3kBwwYALgro2+7MNlXP/HEE4DTkvuSSy4B3Dbq0nZ90aJFRkIXFRXF3L8uLd6mTJnCr371Kzm++f/3338PuG21pQOUdHMKh2SKI6gNsYgjaN68OXv27Kl8LPn8Kt2rvF4vl112GQDvvPMO4Lb3qw1J0/JMmlq8/fbb9O3bF6BGd5jvuCufTNu2je9f+gT6UlRUBLgdladNm2Z+rl+/PgA//PAD4Khq0hcxloJA5v7iiy8CcOWVVxoBJni9XtavXw+4QnPVqlW1/eioCQKZU8+ePZk/fz4ATZo0AVx/d35+Pn/9618BmDt3LgDffPNNKB8TNNEQBOeccw7gLCDg9u/0RYT39OnTzaLXrFkzwJl/vXr1AKfbNbhdwSdMmBDscKug5cwVRQlIwmgEsqqfcsopvP766wDk5uaa/8k4CwsLAcwq7fV6adSoEeBsK8BphioagfxN3m9ZFrfccguA6RYcbPRVLFVmcQdu2bIFcIxJco5k7rNmzWLcuHFAZNRHIdLzlHEPGjQIgOeee45WrVoBNWt9PuMxK6s0uo0EkdIIZA79+/fn6aefBuCEE04AnE7bkydPBtzGtoFo164dAOvWrQNcA3aXLl3M/R8qqhEoihKQhHEfyoq9Zs0a0+xTWmZfdNFFnH766QC88MILAGzfvh1wjGKyd5bXt2zZ0jQKlTbqhw8fBhybwddffx3t6dSa448/HnDmAv5a0ahRowB46623IrpCRgtZMcWA26BBA6OFyXex5VTX+t3j8RhjqBhPE5EtW7Zw3XXXAVBQUABgbDihIMbpZcuWARg7QoMGDcLWCAKRMFuDmrAsy3TGPXDgAEC1XYDlhrMsq8qNFglisTWQLYEYm84880w5ptnuiGFp//794X5MjUR6nhKjIUJ84MCBxpvz4YcfAq4QP++884zw9hUKch3Fe3TPPfcE89E1kqjZhyIU16xZA7gG7BEjRrB06dKwjqlbA0VRApIwW4Oa8Hq95OTkABjV6/777wfg0KFDfpFa4MQOJEpEYKiI2n/GGWcA/j5n8UeL2pksiEbQuXNnwIna3LVrFwDz5s0DXHetbdtm7rISejweo+396U9/AuAvf/mLef2xhmhHovmJMfymm24KWyMIhGoEiqIkh0YA7qpy6aWXAnDhhRcCTsSduGrmzJkDOHurZFwpUlNTGT16NFDVaHb48GEz92Sbm+x5JZ4+JyeHQ4cOAa6LeO3atQBMnjzZ2EVk9Zdr74vYESQnJFmRc9OmTRsABg8eTHFxMQDffvstgNGGO3XqZLTeSM9bNQJFUZJHIzj33HMBN/Oubdu2ADz//PNGqt5xxx0AvPvuu1x55ZWA6zZMBho3bmyCSWTVF2t5eXm58Sj42g2SAZmDjDs9Pd0EFIlbWEKjTzrpJPr37w9UHx4ucxY3oriJkxHLskyw0ciRIwHHVnLvvfcCzr0NcP311wPQvn17hg0bBmCC7iJFUrgP69SpY3IBJDZdIs1SUlKq9T0L4meXG6c2fthouw9bt27NV199BbiGT5mb1+s1ORKbN28GnBgDUZHFzx6JnINIz1Me6IULFwKOS1SE2r59+wAnpwOc6Dm5xr5uxMqFSV9++WXAMR6Hew/Hyn1YWXBLXk1ubi4zZ84E4B//+Afg5Nps3LgRcO/1GTNmAE4chlznk046CXDd6YFQ96GiKAFJCo2gcePGxhAoRhUZd05OjpG44maRlaQ6SkpKzGoUKtHWCOrUqWNcg+GOUfB6vdStWxcIvUhJtOY5cOBAwHEZythk2yC5EhkZGVXyD2zb9ssV8WXjxo0mEjVUoqERyL0ohtGysjJz/sXAJ98rKiqCigyVgjT5+flGU5TzkZaWFlTQnGoEiqIEJCk0Ao/HY1Z5kaCBxu3T2KHK/8R1JW6ZYIlFiPHll18OQF5eHlC9diNzLygoYMeOHYCTtQn+K6bkVBx33HEhjSHa83zllVcYMWKEHKO6zwfca7d//36jQUiuvi9yrNdeey2kcURTI5DaAfPmzTP2rdr2x2jUqJGpZSCf07lzZ2MzqomkKUwSbbp06QK4RilwknYAhgwZEtQxYiEI5EG+6667AEyacUZGhlGfxdL86KOPGrWwffv2gJu2nJqaam488cMHeyNGe56pqamsXr0acNN1xaB48OBBk8r76quvAk4hD0m8kWIlEqVoWZY5LyIsEqHT0dVXXw0491gkc0Ik/0AE/3333cfEiRMDvk+3BoqiBEYMMbH4AuxQvjwej/2TJI7Y180332xXJj09Paj3RmueNc09Ozvbzs7Otlu3bm3n5OTYOTk51b4+LS3NTktLs0tKSuySkhLbtm3zc1ZWlp2VlRX0Z8dinhkZGXZGRoY9depUe+rUqfa2bdvsbdu22b/4xS9qvO5169a169ata+fn59v5+fl+1/Hxxx+3H3/88YjPM5y5NmnSxG7SpElE713AbtOmjd2mTRsz561bt0ZkrqoRKIqS2DYC2S9HsqZAdnZ2lW5ABQUFxvVYE7GwEYSLVC/+6KOPAOfcidtKyrUlio3AF7nGYrgtLCwMao8/ZcoUwOntIEiMvtgKAhFNG0G0cgLEdiTZt8XFxUHNV20EiqIEJKE1ArF2W5ZlwmtrS7NmzUyYprBx40YTslnT+UhEjSA7OxuAJUuWAP5uxBUrVgBuPH+wJOI8K+Nbgk7CzUVzTE1NDUqriIVG4PV6a+029EW0Hnk2zj77bNPlqiYCzTWhk44kZqBr167G9y+x+OGyYMGCKn8bO3ZswibwyAW3bbtKFFqvXr1MJWapcSjz8Hq9PPTQQzEcaWyRc7F+/Xp69OgBuL71hg0bRq2MW7CIUGrbti07d+4Eah9H8NBDD1XZcgQjBIJBtwaKoiS2RiASdMOGDSZLbfbs2YBTtgkCGxJllejduzfgqM6yzRBD1eLFiyM78AggZapeeuklwNGKJKhG5uQbdSh/k7Trf/7znyb45ljGNzJRfh48eLAJRooXcu8ePHjQtJ+T/AOJDqyOlJQU816JopT8mmHDhjF27FjAfQ4ihWoEiqIktrHQFyllJUY9kf4VFRXGTSb7p5KSEuMyqy6T7e233wZcF4zUjw9ELIxoMq9rr70WcPveHS0bsXL2npT7njx5cth70mQwFkpI9VdffVXlGi9evJgLLrgAqFljjKaxUMjMzDTu6mC7OlX+WewdAwcONCHGoRJorkkjCARJyZQquHXr1q2xMIkgse1Dhw4Nu6lmPPzrUr9v/Pjxpimm3NwbN27khhtuAFxBGWrKcXUksiCQ8/Lmm28CcMkll5gHRnpd5ObmGut6TcRCEIBbFEcqcIuwBv/FC5w6hZ988gkAzzzzDBAZg6DGESiKEpCk0wiqOSbdunUD3HqGf/zjH83q8OSTTwJEpB58Iq+UkSSR5ymVnF955RXA0QhlNZV0a+n/EIhYaQSJgGoEiqIEJOk1gliSyCtlJEnkeUpwjrjivF4vDRo0ANyCM8GiGoGLagSKoqhGEAqJvFJGkkSepwRanXzyyQB88MEHYR9LNQIXFQQhEK0HRFxiPkUw4koiC4JIooLARbcGiqLEViNQFCUxUY1AURQVBIqiqCBQFAUVBIqioIJAURRUECiKggoCRVFQQaAoCioIFEUhxlWMj/V4bcGyLPun10d3QFFCcw2qkghz9Xg8Yd9TSd3gJFlJVgGgJDbRvK90a6AoigoCRVFUECiKggoCRVE4Ro2Fffr0YcyYMYDb9OJ3v/sdQJWOwoqiqEagKApJVLMwPT0dwHQE7tq1K+DU+xs/fjzgdgdu2rSpeX3btm0Bt9T1sGHDwu5+nAz+dal/2KVLFzZt2gQQcg/EZJhnJEi2OILacEwUL7UsixdffBGAyy67DMA0OQW3FfikSZMAePTRR00/xDvvvBOAiRMnAk7b6dzcXMCtkR8ssXhA5EHOyMgAoKysDHAeZrlW0i9vwIABpgegvL46pFdi586d2bp1a8AxxGKeIrSlmem4ceMAp9fjhx9+CMA999wDYJqIRppoCAJZgHJycgAoLCw051++y735s5/9jNdeew2A7OxsGZNpmy73/F133WX+Fy5avFRRlIAkhUaQnp5uet0NHjwYgKysLMDRBi655BKg5hr3f/3rXwEYO3Ysr7/+OgBXXHFFSOOI9kppWRYXXnghAL/+9a8BGDJkCOBoBI0aNTKvC4cjR45w9dVXAzBnzpyjvi7S85TV/5FHHgGca3j88ccDjoYWCNu2adKkCeC2CI8EkdIIZIUfMGAA06ZNA9z+CwUFBfzwww8AHDhwAICePXsCjhZXuZO3bdtGc/jxxx/9jlVTi/dAqEagKEpAkkIjyMnJYdGiRQCceOKJgNMFFyAvL8+scjXRpk0bADZv3mz2ZaNHjw5pHNHWCDIzM1m4cCEAPXr0ANx5WpZVZfXwer3GznHjjTcC8N///lfGys033wzAY489Zl7/8ccfA9CvX7+jjiMS85Sxtm7d2mhjP//5zwHHxiFaTeU51TAmwL2Ou3fvDup9AY4ZURuBZVk0b94cwNyT/fr149RTT5XPA6C4uBiAxYsXGxuWaA0NGzbk/fffB9zu3tLnMZo2gqQQBFlZWWzevBlwvQZiCW/VqhUFBQUBjyEP1Pz5843xZdmyZSGNI9qdjoYMGWJUy3379gHwwAMPAPCf//zHeD7kRiotLa3xuGJAlNcDRqAOGDDgqO+LxDzlJl68eLHZxtWpUweAzz77jPfeew+Av//974A7F4/HY16/YsUKwDFyVr5P+/btC8BHH30UzFCrJRZeg5YtW5oxzp49G4C7774b8L8uvkyePBmAa665BsAIl9qgWwNFUQKSFJGF2dnZxlgkq+dXX30FuAaVQIgbbsuWLcbdmCgMGzYMcNxlq1evBmDQoEFA7SIhhw8fXuVvEmEZbeQ6LV++3Ghvn3/+OQDPPvssR44cqfZ9tm0bzadXr14AzJs3z2xlxPC4dOlSABYsWGAMyInIoUOHjHYnxtKjaQLgnLcuXboAGC04FqhGoChKcmgEZ511ltkjbtiwAXANT8HaOHwjEyVgI97I6vbUU08BjnvvN7/5DVD7nIg+ffrwwgsv+P1t7dq1ZlWONmLMGzlypDEISiBUsJGOohlceOGFLF++HHBdb8K5554bkfFGi9TUVGP3EYNgdcg56tu3r9EEnnvuuegP8CdUI1AUJTk0gvPPP98EU8ycOROAPXv2hHSME044AXA0gqKiosgOMEzq168PuNb9JUuWBBUCXB2yorRq1QqA999/34Rhy7k788wz41JGTT5T7DQpKSlmvMGMp6KioootSN4XyQCjaHDyyScbD4doBr7aXseOHQF46aWXAMdD8OWXXwIYu9iWLVuA6JYqSwpBsGTJEm655RYARo0aBcBbb70FEFDVlci17t27A45PXSK84k1hYSHgxtS/+uqrIb3fsiwTVyGxERKxl5mZaVRw8ePH20gqN3J5ebkxJgZzc1uWdVThPX369MgNMAr06NGDESNGAK5he+7cuYCTa3DHHXcAriAvKSkxWwhx9YrgOPvss/niiy+iMk7dGiiKkhwBRW3atGHHjh1yDMA1JP3sZz+rNqhENIHjjjsOcCMSFy1adFTXVSCiFVAkgTZpaWlBZdpJZtsbb7zBeeedZ97ry+HDh00UXqgaUCzTkIPZIrRq1Yp3330XgG7dugHudic3N5ddu3aF9dmxCCjq06ePieaUMYt2k5qaaq6b/G38+PFs3LgRwARdiVEZ3EAw0RaCRQOKFEUJSFLYCHbt2sXbb78NuG5Dyd/Oy8szey4pONK0aVM6deoEuPviWbNmAYHDcuOBBJhdBZ4eAAAQgklEQVQ0bdrUzEXCSiXOfPXq1cZodNppp5nvsqKKPeDJJ58EYMKECUG5ICX0unXr1kGFakca0QR8sxBllRRN6bLLLqNx48aAu6pK4FWoRuNY8+mnn5oVXUKnW7ZsCcD27dvNfKpzqYoRWUKte/bsafIQ5HxE6polxdYA3Bv2/vvvBzAGmLS0NHOCJVbAtyOMPGRS7GLWrFnGQhsq0VaZfbcGlQuNlJWVmS2NPPyZmZlmfmI0u/3224Hg4xDkWB6Px9yU8axQZFmWEQSSdv3www+bdGy51lOnTgWc+YabnptsFYr27NljFghZGOW8BEK3BoqiBMa27Zh9AXZtvzwej+3xeOx27drZ7dq1s5999ln7wIED9oEDB+ySkhK7pKTELioqMl8VFRV2RUWF7fV6ba/Xa5eWltoZGRl2RkZGyJ8di3muWrXKXrVqlS3IuEtKSszPMqfdu3fbbdu2tdu2bWtblmX/1HOx1l+xvJ41XePMzEw7MzPTfvDBB+19+/bZ+/bts8vKyuyysjJ7yZIl9pIlS+y6detGfZ7RnGsoX6NHj7aLi4vt4uJie//+/fb+/fsjNlfVCBRFSQ5joS+y9xcj0Xvvvcfzzz8PwMqVK/1eA3DVVVcB8PLLLwPOPlyKePztb3+LzaBDQAqwSgSl4BuNJ9+XLFliXGfxiBiMFjIX3/mKe02MZOJGrFevXsJEikYLsZmMGTPGnBMxgluWVasSZoJqBIqiJJ9GIMiqsXLlSr7++uujvk7Cdi+99FIAhg4dakpoJyISKCJzkko/derUMXOWWgyjR48+pjSBo5GRkWG8KCUlJYBbqFbCtI9FZPU/88wzASewSrxE77zzDhA5TTBpBYG4kYJNKZaY7osvvtiol4mGx+OhQ4cOgFvLXxq0gJu0M3ToUCD+uQPRQvzukih20UUXmQQq2QZIJeqainwkO3Kfiqu8oqLCJKVV3jrWFt0aKIqSfBqBqEsDBw4EnAhD6XlQXXSWBBk9/fTTgKNKSSGQREHm1LZtW1NMpEGDBoCbU+H1eo0GsH379jiMMnY0bNgQgNtuuw3wTx3Pz88HYpOaGy/knhUDt2iFH3zwgalILZqBZVkht7SrDtUIFEVJPo1A8thPOeUUwCljJX0NpSiHbdtmPy2hyRLLXlpaago/JAqSN9GvXz9jHBTEGLZs2TKzGiZivkQkkZoKUrC0Tp06Jqb+m2++AQi7gEskkXsqEiuyaIU5OTmMGTMGcI2E//rXvwD4v//7vyqZpCkpKRH5/KQTBDLpP//5zwA89NBDfPrpp4B/roEkrEjMvVS9HTNmTMIZmEQQnHzyyabiraRWy/9mzZplkqpqW88w0fn2228BN9nmnHPOMf9btWoVkBiG0pr89zWlV4sA8c2TkQXummuuMVWtJS7mpptuAqo3jEZCCIBuDRRFIQk1gsocPnzYRJmJFJZVFFyJLCtIIhqXpIRVdna2SVEVg1m7du0A6NKli/EdH+tIKzopJtOwYUOjBZ188smAu+WLVsv0YKjpXvL9n2gAsnWVBrfNmjVj7969gOsyHTVqlDEUy/WOhQarGoGiKMmvEfgiUjieq0Q4iGtswoQJJqBI6gtIibZNmzYlpDYTDW644QbAbQdu27axnUgAWW00gmAbr0YKsV399re/BTDXePbs2cY2IEbi/fv3G9doXl5ezMaoGoGiKMlToSgRiGflnlgS73lKtp3YSX788UfjDhYicd/GukJR5XyJSscHHO2hXr16AKYiVSQ8JIHmqoIgBOL9gMQKnWdVYjlXMRzK90gYC7VUmaIoAYmpRqAoSmKiGoGiKCoIFEVRQaAoCioIFEVBBYGiKKggUBQFFQSKoqCCQFEUVBAoikKM05D/V2LTdZ7JQaLmGkQDzTVQFCUgKggURVFBoCiKCgJFUVBBoCgKx1jxUkVJNqRE2dlnnw3AwoULTel2+VssOnOpRqAoSvLULJSyz9WNd/ny5QD07NnT/G3WrFkAjBs3DoDvvvsu3I82qH/dn1DnKWW9vV6vafYh10Xq8sXyfox1HIE03pHehsOHDzfNeaR9WmpqqvlZiriOGjUKcLsjh8MxU7x0//79gNMkEtwbJzMz0wiJmvj4448BV90Kh3gIAlEd09LSTHXb8847D4BJkybRuHFjADZu3AhA//79gdoVvIz0PKVm/8KFCwHo2rVrlWsm92FRUZHpYSBz37Ztm7nu9evXB9zKvnfeeSfvvfdeMMOoQiwEQUpKCldccQXg9OkEaNSoEeA8/J988gkA48ePB2Dt2rWm2vHatWsBt7/Dtddey5w5c8IZhgYUKYoSmKTQCOrVq2c0AukC86tf/QqAzZs3mzrxvnMRKSpttKWddKdOnaq0lg6WeGgEM2fOBGDgwIGmJ15NGpDUwm/evDmHDh0K6zMjPU9Z2e+9917AWcVF7a0tZWVlnHrqqUDoRrVoagRyja6//nrTuVv6HD755JOA0+5crlF1XY1FA3z//fcBKCwsZODAgaEMw6AagaIoAUkKjWDFihWcdtppgNvzLtg9cH5+PgA//PADAN27dw+7p3wsNQKZ5+7duwHH0CSajGhHKSkp5Obmmp/BNToNGDCADz74IKzPjvY809LSOOWUUwC3H+Dw4cMByMrKMqupzMXj8VTpVyj/KyoqMseQXoHifgtENDUCMYzu3buXrKwsAHr16gXAF198EdQxRAOcPHkyAH369DEagWgXwRJorkkRR9C0aVPzc7ACQG6m5s2bA267qXCFQKyQG/7hhx8G3Jbpw4cP58MPPwTchwDcecrNL7/369cvbEEQbcrKylixYgXgWsTlO7jnQLZ3I0aM4KabbgKgY8eOgL8XSbZ/bdq0AZzGsfHu1yH3WXl5udm6rlu3LuD7LMsyAmDYsGEA1KlTB3AMwqWlpdEYrm4NFEVJEo3gyJEjIUv4Tz/91O/3lStXRnJIUUPGffzxxwPw+9//HuCoq7uv+uzL1q1bozXEqCPXWrZzN954ozkfsgXyfa1oe7INjLc2AK5GsH79epo0aeL3t5rwer1mjosWLQJcY2F+fr5qBIqiRI+k0AiKi4tDCpBZsWIF3bt3B9yVccCAAVEZWyRp1qwZPXr0AFzD14wZM2p8T+vWrf1+Lyoq8nt/MiNGtk6dOlWJLF29ejUAo0ePZs2aNfEZYBA899xzXHzxxUG/3rIsc6+La1GuaTRRjUBRlOTQCGbMmMEtt9wCuHth332ghHC++uqrgLOPFEuyuKmSgaVLl5Ka6lySSZMmAYH3uy+88ILf7z//+c+Del8ycP755wP+AVRlZWUAXH755YATfpzILF261Nyf4hKuboWXOV511VVGE5Jw4ljkYSRFHAE4LiFwT4640kaOHMmll17q99ry8nKmTp0KuDkGs2fPBvxdb6ESLf+6CLdvvvnGxOWLy6gmA5PH42H9+vUAdOnSBXB9z+FGT0L8k6vat28PuEk2Z5xxBgcPHgTgnnvuAeDpp5+u9efEKulIjJhyncUgXFxczJAhQwD8Ii3lwZctz4QJEwD46KOPwh2CRhYqihKYpNEI+vTpA7irREFBAeDEX3fo0AFwXYT/+te/jOooElcCbjIzM4OOPKtMtFZKcRetXLmSdu3aAW7GXnXuIllZbr31Vh588EHATXE94YQTgNq5D+OhEcg5mD59OldeeSXgam/5+fmcfvrp5udIESuNQFy/kjUaiMr3p/zepUsXoxmHimoEiqIEJGk0AkGMKrICHjx4sFojisR6i2FGXjN69GheeumlsD47WiulzGnevHlm5ZOQ282bN5vXtWzZEnC1hAULFhibQOViFrUhlhqBhNHOnTu3yv/EPrJmzRp69+7t97dIECuNQLSdnTt3Am7otGVZRruT63fgwAHjNhSt0Ne20Ldv37DGcEzkGvgiJ6ywsLDG18nDIimqYiwcPHhw2IIgWsicXnzxRWMkvP766wHMtic7O9t4CMQ7UlFRYYSIpB8nCyLoXnzxxSr/E6H9/fffA845eOyxxwC47bbbYjTCyCHCSypoybXyjZiVh71Ro0ZGOErattwTDRo0MAtcpCMMdWugKErybQ3C+EwANm3aBDjZiKJOhzr3WKjMog7K6rF9+3bAv1zXoEGDAJg2bZpZbd566y0AfvnLX4b70YZYzFPKcHXu3BlwS4/dfPPNJsVWDMT333+/uY6SyScRlQUFBWH712O1NRCtLTMzE3DnerRxSxyBlJ+T7NvDhw+bWo9yHoJFjYWKogTkf0YjEJtCZmamkbihFviMd6DNWWedBcB///tfwFlpdu3aBWAKlNQmYEqIxTz79esHuDkgjz76KOBcJ8kmFLdb7969ayzPJvfwnXfeCTilwILZQ8faWChangQKBXJjS1HWCy64AHDmKfUYvv7665DGoBqBoigBSTqvQaj4lsQGxwIdbkBRvDnppJMA/3wLybKMhCYQS6SMtwSBiZs3JSXFuEnnz58PwPPPP29sJzfeeCOACbzydcFNnDgRcIKp3nnnHSD0vXQ0kGtzzjnnAK4mEChr8t///rff+1JSUkyZukiTdIJAknKCfZilhrzkHOzZsyfpHhpBipTI3H/88UcTYZlsSPKQGDsbNmwIwHXXXWci8KZMmQI4D4S8rnJvgF69epltkbjlVq1aFYMZBI9sXWSct956K+C6iCsjgk16Vsi9m5WVFbWUZN0aKIqSPBpB165dATf7UAKFxBVTGTE4vfnmm4C7Ak2YMCFpNQLJyhPj0+9+97s4jiYyyGophUeHDRtmtgHS1cjXoF25jNnChQuNIVECb9LS0sw5Eg1SNIp4pmdLn4Jrr70WcO7pyy67DMB0d+rRowcjRowA3N4db7zxBuBoQ3IfRxrVCBRFSR6NQLIIO3XqBGDy02fMmGH2krKStGzZ0uzDRJOQ0laJtn8MBQkvlVXt9ddfj+dwgkbyH0QT880XkGIdI0eONK/dsGED4AaBVS7MWhk5rrgMy8vLE7Iwy9133w04dhBw3KKSf+CLzEfc21JzQnpcRIOkiyOQZpFSwcf3JhEjmsfjMYU5JMfg5ptvru1Hxz2OQB4g6QkgiTiRJpLzTE9PNxZ+id/Yvn27EWoivKUCVVlZmblm4lEoLS2NSj+KWHdD9jkWAM8++yw33HCD3/8qKiqqNGyRRa82aByBoigBSTqNQBAj0Lhx4xg7dizgNsE88cQTeeKJJwC3pFWyRNwdjczMTJOe+sc//hFwXWmRJpLztCyLtm3bAm5bs549e5r29KIai3Fv+fLlpvGrtAYrKSkJW9WvrsalEC+NIB6oRqAoSkCSViOIB/HUCFJSUowNRIqXiK0g0kSrLbrYBfr27WtKzok7+NlnnwUcDUG0A7HzhGMfkM8UN7JEGFZyRapG8BOqESiKohpBKMTbayBx9tOmTQOCD7MOlXjPs7K7MJx7VErZSStyydj01S5UI3BRQRAC8X5AYkW85xkJQSC5CxLDIMk6vsJTBYGLbg0URYmtRqAoSmKiGoGiKCoIFEVRQaAoCioIFEVBBYGiKKggUBQFFQSKoqCCQFEUVBAoioIKAkVRUEGgKAoqCBRFQQWBoiioIFAUBRUEiqKggkBRFFQQKIqCCgJFUVBBoCgKKggURUEFgaIoqCBQFAUVBIqiAP8PEUvrLMlp2EwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".........."
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "........."
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "train(datasets, EPOCHS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
